当前位置: X-MOL 学术Am. J. Hum. Genet. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Co-localization between Sequence Constraint and Epigenomic Information Improves Interpretation of Whole-Genome Sequencing Data.
American Journal of Human Genetics ( IF 8.1 ) Pub Date : 2020-04-02 , DOI: 10.1016/j.ajhg.2020.03.003
Danqing Xu 1 , Chen Wang 2 , Krzysztof Kiryluk 3 , Joseph D Buxbaum 4 , Iuliana Ionita-Laza 1
Affiliation  

The identification of functional regions in the noncoding human genome is difficult but critical in order to gain understanding of the role noncoding variation plays in gene regulation in human health and disease. We describe here a co-localization approach that aims to identify constrained sequences that co-localize with tissue- or cell-type-specific regulatory regions, and we show that the resulting score is particularly well suited for the identification of rare regulatory variants. For 127 tissues and cell types in the ENCODE/Roadmap Epigenomics Project, we provide catalogs of putative tissue- or cell-type-specific regulatory regions under sequence constraint. We use the newly developed co-localization score for brain tissues to score de novo mutations in whole genomes from 1,902 individuals affected with autism spectrum disorder (ASD) and their unaffected siblings in the Simons Simplex Collection. We show that noncoding de novo mutations near genes co-expressed in midfetal brain with high confidence ASD risk genes, and near FMRP gene targets are more likely to be in co-localized regions if they occur in ASD probands versus in their unaffected siblings. We also observed a similar enrichment for mutations near lincRNAs, previously shown to co-express with ASD risk genes. Additionally, we provide strong evidence that prioritized de novo mutations in autism probands point to a small set of well-known ASD genes, the disruption of which produces relevant mouse phenotypes such as abnormal social investigation and abnormal discrimination/associative learning, unlike the de novo mutations in unaffected siblings. The genome-wide co-localization results are available online.

中文翻译:


序列约束和表观基因组信息之间的共定位改善了全基因组测序数据的解释。



为了了解非编码变异在人类健康和疾病的基因调控中的作用,识别非编码人类基因组中的功能区域很困难,但至关重要。我们在这里描述了一种共定位方法,旨在识别与组织或细胞类型特异性调控区域共定位的受限序列,并且我们表明所得分数特别适合识别罕见的调控变异。对于 ENCODE/Roadmap 表观基因组学项目中的 127 种组织和细胞类型,我们提供了序列约束下假定的组织或细胞类型特异性调控区域的目录。我们使用新开发的脑组织共定位评分,对 Simons Simplex Collection 中 1,902 名患有自闭症谱系障碍 (ASD) 的个体及其未受影响的兄弟姐妹的整个基因组的从头突变进行评分。我们发现,与高置信度自闭症谱系障碍风险基因共表达的中胎儿脑中基因附近的非编码从头突变,以及靠近 FMRP 基因靶标的突变,如果发生在自闭症谱系障碍先证者中,则更有可能出现在共定位区域,而不是发生在未受影响的兄弟姐妹中。我们还观察到 lincRNA 附近的突变也有类似的富集,先前显示这些突变与 ASD 风险基因共表达。此外,我们提供了强有力的证据,表明自闭症先证者中优先的从头突变指向一小部分众所周知的 ASD 基因,与从头突变不同,这些基因的破坏会产生相关的小鼠表型,例如异常的社会调查和异常的歧视/联想学习。未受影响的兄弟姐妹中发生突变。全基因组共定位结果可在线获取。
更新日期:2020-04-20
down
wechat
bug